My robot is in desperate needs of new parts, so I ordered the Fabrikator Mini v2 from Hobbyking (below 200 EUR with shipping). It has a 10x10x10cm build volume and a sturdy metal frame while it’s only 17cm wide, 18.5cm deep (28cm with the spool holder mounted in the back), and 18cm high, which means it fits in one compartment of an IKEA KALLAX shelf. The first impression is very positive!

In this post I will describe my first experiences, the setup in windows/linux, and which settings work best for me using RepetierHost and Slic3r.

Introducing jupyter-lab

Vim is all fun and games, but for interactivity, storytelling and presenting, or just interactive prototyping, nothing beets jupyter notebooks. Some fine guys have taken it one step further and introduced jupyter lab, which is a wrapper around our beloved notebooks. It offers easier kernel-selection, multi-window notebooks, built-in python consoles and some more.

Autoformatting Python Code

Sometimes, a lot of authors, editors and OSs mess up the indentations and style-conventions of your files.

After I completed the circuitry to power my raspberry pi from a battery pack, I wanted a way to display the voltage of the battery pack, and be able to access the voltage level from the raspberry pi, so it can shutdown automatically when critical voltage levels are reached to prevent damage to the filesystem or draining the battery too much.

The raspberry pi will be the main processing unit of my pypibot. I want to power 6v-motors, so I decided on going with a 7.2v battery-pack. I had one lying around with 2600mAh, which should be enough for testing the setup right now.

I originally planned on going the easy way and ordered a converter from 8-36v to 5v, with a micro-usb-connector already wired (from DROK). Without any other load this worked nicely, although the input voltage was below 8v. But as soon as the motors have been wired up, the voltage would drop too low for this thing to still output 5v, and in consequence the pi went down.

So, here is the definite way to go if you want to power a raspberry pi in a robust way from a 7.2v battery (or anything above that voltage):

Using an adjustable DC/DC power converter! While these units cost little over 5 EUR (for 5 units in total), they take anything from 4V – 35V as input, and the output voltage can be configured by turning a little screw on a potentiometer. In my experiments, the voltage could drop as low as 6.1v, and this unit would still supply a rock-steady 5v to the pi (once setup, it will deliver steady 5v on the output for a wide range of voltages actually). They can withstand 3A max, which should be enough for the raspberry pi and any sensor I hook up to it.

I ended up soldering a micro-usb-connecter to it myself:

In a first testrun with the 7.2V, 2600mA NiCd battery pack I had lying around (it is quite old, so it probably has a far lower capacity than that), the Raspberry Pi lasted 1 hour and 42 minutes, while driving around with the motors from time to time: up 1:42, load average: 0.48, 0.33, 0.33.

So today my Neat XV LIDAR module arrived, and I had to test it directly with the Raspberry Pi. For everyone that does not know this wonderful piece of hardware yet: It is a low-cost 360-degree spinning laserscanner that is usually scavenged from the Neato XV vacuum-robots. In Germany it is quite hard to get your hands on one, so I ordered one via ebay from the US.

It is quite challenging and costly to build up a robot lab, especially if you just want to conduct some experiments with sensors and a moving platform. In todays search of affordable robot platforms, I discovered MORSE, a simulation platform built on the blender game engine (www.openrobots.org/wiki/morse/). This article will show how to set it up, select an environment, add sensors and read from them.

It already has the infrastructure, several environments and pre-built robots, sensors (camera, GPS, laserscanner, IR, etc.) and actuators to play with, and it can be installed directly via apt (Ubuntu + Debian). It took me less than an hour to skim through the tutorials, set up a basic environment, add a laser-range sensor to an existing robot and visualize the results, pretty amazing! (You can find all of my project files here: https://github.com/TobiasWeis/morse-robot-simulation)

I had a little free time on my hand and decided to quickly complete the coursera-course „Data Science at Scale – Practical predictive analytics“ of the University of Washington by Bill Howe. The last assignment was to participate in a kaggle competition.

For this assignment I chose the „San Francisco Crime Classification“ challenge. The task is to predict the Category of a crime given the time and location. The dataset contains incidents from the SFPD Crime Incident Reporting system from 2003 to 2015 (878049 datapoints for training) with the following variables:

So I also decided to build myself a smartmirror. However, I want it to provide a little more functionality than just displaying some information and telling me that I’m beautiful. Here is the finished build:

And here is a video of the leap-motion-control in action:

I want to place it in my bathroom, because that’s the only place where I actually spend some time in front of the mirror. I do want some controls, but I do not want to touch buttons or the mirror itself, so I chose a leap motion controller. Below I will detail some of the steps I went through in building this thing.